Cohere Getting Started: Account, Keys, and First API Call (2026)

Getting started overview

This guide provides a focused walkthrough for developers to initiate work with Cohere's API, covering account creation, API key retrieval, and making a foundational API request. Cohere offers access to various large language models (LLMs) and embedding models, including Command R+ and Command R for generation, and Embed v3 for semantic search. The API supports a range of tasks from text generation to summarization and reranking.

The core steps involve:

1. Registering for a Cohere account.
2. Generating and securing an API key.
3. Installing a Cohere SDK (Python is used in this example).
4. Executing a simple API call to verify setup.

A free tier is available for new users, offering generous allowances for initial development and testing, including up to 5 million input tokens for Command R models monthly and 1 million input tokens for Embed and Rerank models monthly, as detailed on the Cohere pricing page. This allows for experimentation before transitioning to a pay-as-you-go production tier.

Quick reference table

Create an account and get keys

Access to the Cohere API requires an account and an associated API key. This key acts as your credential for authenticating API requests and is essential for interacting with Cohere's models.

1. Register for a Cohere Account

Navigate to the Cohere registration page. You can sign up using an email address, or through single sign-on (SSO) options like Google or GitHub. Complete the registration process by providing the required information and verifying your email address if prompted.

2. Obtain Your API Key

After successful registration and login, you will be directed to the Cohere dashboard. Your API key can be found in the API Keys section of the dashboard. Cohere provides a default trial key upon account creation. Copy this key, as it is required for all API calls. It is critical to treat your API key as sensitive information and protect it from unauthorized access, similar to how you would handle other API credentials such as those for Stripe API keys or AWS access keys.

Your first request

This section demonstrates how to make a basic text generation request using the Cohere Python SDK. This example uses the generate endpoint, which is a common entry point for interacting with LLMs.

1. Install the Cohere Python SDK

Open your terminal or command prompt and install the Cohere Python SDK using pip:

pip install cohere

2. Write Your First Python Script

Create a new Python file (e.g., cohere_test.py) and add the following code. Replace YOUR_API_KEY with the API key you obtained from your Cohere dashboard.

import cohere
import os

# It's recommended to load your API key from environment variables
# For this quickstart, we'll use a placeholder, but for production, use os.environ.get()
COHERE_API_KEY = "YOUR_API_KEY" # Replace with your actual API Key or load from environment

try:
    co = cohere.Client(COHERE_API_KEY)

    # Example 1: Basic text generation using the 'Command' model
    print("\n--- Running Generate Example ---")
    response_generate = co.generate(
        model='command',
        prompt='Write a short, engaging blog post about the benefits of remote work.',
        max_tokens=100,
        temperature=0.7
    )
    print("Generated text:", response_generate.generations[0].text)

    # Example 2: Embedding a text (using the 'embed-english-v3.0' model)
    print("\n--- Running Embed Example ---")
    texts_to_embed = ["Hello world", "The quick brown fox jumps over the lazy dog"]
    response_embed = co.embed(
        texts=texts_to_embed,
        model='embed-english-v3.0'
    )
    print("Embeddings for 'Hello world':", response_embed.embeddings[0][:5], "...") # Print first 5 elements

except cohere.CohereError as e:
    print(f"An API error occurred: {e}")
except Exception as e:
    print(f"An unexpected error occurred: {e}")

3. Run the Script

Execute the Python script from your terminal:

python cohere_test.py

If successful, the script will print the generated text from the generate endpoint and a truncated embedding vector from the embed endpoint. This confirms that your API key is correctly configured and that you can communicate with Cohere's services.

Common next steps

Once you have successfully made your first API call, consider these next steps to deepen your integration and explore Cohere's capabilities:

• Explore Different Models: Experiment with other Cohere models, such as Command R+ for advanced reasoning or Rerank v3 for improving search relevance. Each model is optimized for specific tasks.
• Review API Reference: Consult the Cohere API reference for detailed information on available endpoints, request parameters, and response structures across all services.
• Utilize the Cohere Playground: The Cohere Playground is a web-based interface that allows you to interact with models directly, test prompts, and observe responses without writing code. It's an effective tool for rapid prototyping and understanding model behavior.
• Implement Error Handling: Integrate robust error handling into your application to manage API rate limits, invalid requests, and other potential issues gracefully.
• Secure API Keys: For production environments, ensure your API key is not hardcoded. Instead, load it from environment variables or a secure secret management service. This practice aligns with general security recommendations for managing sensitive credentials, as described in Google Cloud's API key best practices.
• Explore Advanced Features: Look into features like conversational memory, fine-tuning models, or integrating with vector databases for RAG (Retrieval Augmented Generation) applications.
• Explore SDKs in Other Languages: If your project uses a different language, explore the official Cohere SDKs for JavaScript, Go, or Java to integrate Cohere into your preferred development environment.

Troubleshooting the first call

Encountering issues during your first API call is common. Here are some troubleshooting steps:

• API Key Issues:
  • Incorrect Key: Double-check that you have copied the entire API key correctly from your Cohere dashboard. Ensure there are no leading or trailing spaces.
  • Expired/Revoked Key: Verify that your API key is active. If you suspect it might be compromised or inactive, generate a new one from the dashboard.
  • Environment Variable Not Loaded: If you are loading the API key from an environment variable (recommended for production), ensure the variable is correctly set in your execution environment. For example, on Linux/macOS: export COHERE_API_KEY="YOUR_API_KEY".
• Network Connectivity:
  • Ensure your development environment has an active internet connection and can reach api.cohere.ai.
  • Check for any firewall rules or proxy settings that might be blocking outbound HTTPS requests.
• SDK Installation:
  • Verify that the Cohere SDK is correctly installed. Re-run pip install cohere to ensure all dependencies are met.
  • If you are using a virtual environment, activate it before installing and running the script.
• Model Availability and Parameters:
  • Confirm that the model name specified in your request (e.g., 'command', 'embed-english-v3.0') is correct and currently available. Refer to the Cohere API documentation for a list of supported models.
  • Check that all required parameters for the endpoint are present and correctly formatted (e.g., prompt for generate, texts for embed).
  • Review any error messages returned by the API. Cohere's API errors are typically descriptive and can guide you to the specific problem. For instance, an error like 'invalid_request_error' often points to missing or malformed parameters.
• Rate Limits:
  • For trial accounts or specific tiers, there might be rate limits on the number of requests you can make within a certain time frame. If you hit a rate limit, the API will return a 429 Too Many Requests status code. Implement retry logic with exponential backoff if you anticipate hitting these limits in a production application.